Hydraulic actuators are widely used to drive robotic manipulators in industry for tasks such as earth moving, material handling, construction and manufacturing automation due to their large power-to-mass ratio. However, precise control of hydraulic actuators is more difficult than control of conventional electric motors due to the presence of non-linear flow-pressure characteristics, such as: variations in the trapped fluid volume in each actuator chamber; fluid compressibility; friction between moving parts; variations of hydraulic parameters; presence of leakage; and transmission non-linearities.
Much of the work on hydraulic control relies on linear control design methodology that is based on local liberalization of the actuator dynamics about a nominal operating point. However, these methods suffer from two major drawbacks: First, since the actuator dynamics are highly non-linear, a single linear time invariant controller can be only tuned for a particular operating point and the performance degrades as the system state moves away from the operating point. Second, since the dynamics of actuator and load are coupled together, the dynamics of the load (which can be very complex) are implicitly embedded in the linearized model of the actuator, which complicates the treatment of the situation; it is then difficult to achieve precise control. As a result, these methods rely highly on the knowledge of the load characteristics and variation in those characteristics.
Mechatronics systems, such as electro-hydraulic robot manipulators, are essentially multi-dimensional non-linear systems composed of mechanical and actuator subsystems accounting for load dynamics and actuator dynamics, respectively. The control problem can be greatly simplified in many applications, if actuators behave as an ideal source of force/torque with low impedance, i.e. similar to electric motors. However, the force/torque generated by a hydraulic actuator is affected by its own motion resulting in a coupled dynamics of the actuator and load.
To account for parametric uncertainty of estimated and/or somewhat inaccurate parameters, non-linear adaptive control methods have previously been employed. An adaptive robust method can also be used, which takes the nonparametric unmodeled dynamics into account by assuming a known bound on the nonparametric uncertainty.
Dynamic feedback linearization has been used to attempt to cancel out the actuator non-linear dynamics. The advantage of this method is that for force control purpose, no knowledge of load dynamics is required because it cancels out the effect of velocity perturbation. However, in practice, exact cancellation of the actuator dynamics is not possible due to parametric and nonparametric modeling uncertainties. This problem has been addressed by transforming the linearized system into standard linear fractional uncertain structures; however, no method has been presented for computation of uncertainty bounds.
The control of a torque/force output is very different in nature from known attempts to control motion or position. When a controller is for controlling a system in which there is no motion, or negligible motion, much of the hydraulic behaviour is masked, and friction is the main observable factor affecting the system. This is one reason why many known systems seek to compensate for frictional components. It is also necessary to consider the dynamics of the whole system together, namely the combination of the actuator and the load. In torque/force control situations such as those discussed according to embodiments of the present invention, it is necessary to consider the effect of velocity on the system; as such, the torque/force control problem is quite different in nature from the motion and displacement control problems.
It is, therefore, desirable to provide a procedure for identification of actuator non-linear dynamics and quantification of modelling error. Most existing adaptive methods deal only with parametric uncertainties and some robust adaptive schemes assume a known bound for non-parametric uncertainties in actuator non-linear dynamics. No method is known to estimate this bound, and attempts to account for non-linear dynamics have drawbacks.